Aug 15, 2019 · In this paper, we derive some error estimates in continuous norms for the discrete least-squares function approximation by radial basis functions.
Nov 1, 2019 · are comparable to kernel-based interpolation in cases which the function it is approximat- ing is within and is outside of the native space ...
Aug 15, 2019 · In this paper, we derive some error estimates in continuous norms for the discrete least-squares function approximation by radial basis ...
Nov 22, 2022 · We study the stability and accuracy of approximation methods using the Gaussian RBF in all scaling regimes of the associated shape parameter.
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In this article we study the convergence behaviour of least squares approximations of various types by radial basis functions, i.e. least squares ...
The RBF solution is computed at discrete times and the approximation is expressed in terms of the coefficients of the basis functions. Here we use a ...
Aug 15, 2019 · We consider discrete least-squares methods using radial basis functions. A general ℓ2-Tikhonov regularization with W 2 m-penalty is ...
Discrete least-squares radial basis functions approximations. Applied Mathematics and Computation, 2019. By Ka Chun Cheung. See Full PDF. Download PDF ...Read ...
We consider discrete least-squares methods using radial basis functions. A general ℓ ² -Tikhonov regularization with W 2m -penalty is considered.
Abstract. Moving least squares (MLS) and radial basis function (RBF) methods play a central role in multivariate approximation theory.